Large-scale data processing systems are often used in hosting mission critical software applications. For example, an airline may have one or more large scale systems that host its passenger reservation application and various other related applications. Banks, retailers and other businesses have analogous data processing needs.
With the advent of Web browsers, a great deal of business is being conducted over the Internet, and customers have close interaction with business' data processing systems. For example, a traveler may purchase a ticket directly from an airline via the airline's web site, a bank customer may pay bills via the bank's Internet-based bill paying service, and countless customers buy goods from retailers over the Internet.
The performance level of a business's data processing system may influence a current transaction being conducted with a customer, and might also affect the customer's future decisions in selecting with whom to do business. Thus, if the business' data processing system performs slowly in interacting with the customer, the customer may turn to a competitor in hopes of faster service.
Many factors may influence the level at which a data processing system is able to perform it's programmed functions. The factors include the particular hardware and software configuration of the system, as well as the processing load being placed on the system. Example system hardware characteristics that influence performance include the number and speed of CPUs, the amount of memory, the I/O bandwidth and the characteristics of many other system components. Example software characteristics might include configuration settings that control buffer sizes, numbers of active threads and other measures taken by software to self-impose limits on the consumption of system resources. The performance level of a data processing system may also be influenced by a varying processing load. For example, in the customer interface applications mentioned above the number of users interacting with the system will influence the system's performance level, and the number of users may vary by time of day, time of month, or time of year.
The responsibility for maintaining a system at an acceptable performance level is with the system administrator (SA). Addressing performance-related issues is generally best done by an experienced SA. It may take many years of working with a particular class of system before an SA is able to quickly identify and address a performance problem. Furthermore, the ability to assess when a system will begin to exhibit performance problems may also require considerable systems administration experience. The number of highly experienced SAs is generally much less than the need for their expertise. Large-scale systems are found in businesses worldwide, and the need for specific expertise may arise at any hour of the day.
A system and a method that address these and other related problems are therefore desirable.